Search Results - (( java application optimisation algorithm ) OR ( brain computer work algorithm ))
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Extended development of a Computer Aided Detection (CAD) system for brain bleed in CT / Muhammad Illyas Abdul Muhji
Published 2018“…The new develop algorithm is set to register image of brain patient in order to determine the rotation angle for brain realignment. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Brain machine interface based wheelchair control with minimal subject training
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Working Paper -
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Context Independent Expectation Maximization Algorithm for Segmentation of Brain MR Images
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EEG signal classification for real-time brain-computer interface applications: a review
Published 2011“…Brain-computer interface (BCI) is linking the brain activity to computer, which allows a person to control devices directly with his brain waves and without any use of his muscles. …”
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Proceeding Paper -
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Investigation Of Edge Detection Techniques Based On Brain Tumor Images
Published 2018“…However, from visual perspective, Sobel operator produced better edge maps of the brain tumor compared to the Modified Canny algorithm.…”
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Deep learning segmentation of brain ischemic lesion from magnetic resonance images for three-dimensional modelling
Published 2025“…This work aims to develop a computationally economical automated brain infarct segmentation from T1-weighted Magnetic Resonance Imaging (MRI) using convolutional neural network architecture U-Net, but with reasonable accuracy compared to existing algorithm. …”
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Brain tumor image segmentation using deep learning approach
Published 2022“…Deep learning algorithm is able to provide good tumor segmentation results compared to other conventional segmentation algorithms as it learns from the labeled brain MRIs to predict the location of tumor region and consequently segment the tumor. …”
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Final Year Project / Dissertation / Thesis -
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EEG EYE STATE IDENTIFICATION BASED ON STATISTICAL FEATURES AND COMMON SPATIAL PATTERN
Published 2019“…EEG signals is one of the main sources on the implementation of Brain-Computer Interface (BCI) technology. It is a non-muscle communication link between brain and external device, which enable the neurologic patients to interact with the world through the brain signals. …”
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Final Year Project -
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…The use of sensors known as Brain-Computer Interface (BCI) tool can monitor the physical processes and mental states that occur in the human brain. …”
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Brain machine interface: classification of mental tasks using short-time PCA and recurrent neural networks
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Working Paper -
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Recognition of motor imagery of hand movements for a BMI using PCA features
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Working Paper -
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Functional link PSO neural network based classification of EEG mental task signals
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Working Paper -
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Advanced neural networking and classification techniques for human brain tissues diagnoses: segmenting healthy, cancer affected and edema brain tissues
Published 2019“…In this work, automatic brain tumor detection is proposed segment the Region Proposal Network (RPN) by Faster R-CNN algorithm. …”
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Multivariate EEG signal processing techniques for the aid of severely disabled people
Published 2022“…Two fundamental objectives for BCI based on motor movement imagery from multichannel signals are aimed at in this research work: i) to develop a technique of multivariate feature extraction for motor imagery related to multichannel EEG signals; and ii) to develop an appropriate machine learning based feature classification algorithm for Brain Computer Interface. …”
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A Proposed Frame Work for Real Time Epileptic Seizure Prediction using Scalp EEG
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Conference or Workshop Item -
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Development of Acute Stroke Lesion Segmentation Algorithm in Brain MRI using Pseudo-colour with K-means Clustering
Published 2021“…The development of an automatic segmentation algorithm was successfully achieved by entirely depending on the computer without human interaction. …”
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